Artem Molchanov

Artem Molchanov

Description:

I'm a Ph.D. candidate in the Robotics Embedded Systems Laboratory (RESL) at the University of Southern California advised by Gaurav Sukhatme. My research interests are focused on systems that have to operate and adapt under sparse, noisy and incomplete information. Most relevant to robotics, this scenario requires careful leveraging of indirect sources of information to make intelligent decisions, such as priors acquired through simulation, additional sensors nontrivially measuring relevant quantities, communication with other agents, different indicators of task progression. Lately, I have been working in the areas of reinforcement and imitation learning, where I am investigating learning under sparse rewards and a sample efficient adaptation to new tasks by combining simulation, automatic task curriculum, and meta-learning. I applied my research to a variety of platforms including robotic arms, underwater vehicles, and autonomous cars. More details about my research you can find on my website.